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Forecasting Oil Production Time Series with a Population-Based Simulated Annealing Method

  • Research Article - Computer Engineering and Computer Science
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Abstract

This paper addresses the oil production forecasting problem, closely related to the estimation of reserves remaining in oil fields. We present a new method, named SAM-oil, which combines simulated annealing metaheuristic with evolutionary computing techniques, statistical analysis and quality assessment of solutions. The method implements a learning-based scheme for pre-processing, modeling and forecasting of monthly oil production time series. Accuracy of point forecasts is compared between SAM-oil and a typical technique in petroleum engineering, known as decline curve analysis, as well as with well-established forecasting methods such as ARIMA, neural networks, and some members of the exponential smoothing family. For the study case, a clustering process has been conducted in order to map forecasting difficulty for three clusters of time series. Our experiments evidence that SAM-oil’s is a very competitive method in oil production forecasting: SAM-oil’s forecasts outperform, in average, those from decline curve analysis and the other forecasting methods, both for the clusters and for the whole set of the experimental time series.

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Authors and Affiliations

  1. Instituto Tecnológico de Ciudad Madero, Tecnológico Nacional de México, Ciudad Madero, Tamaulipas, Mexico

    Juan Frausto-Solís

  2. Mexican Petroleum Institute - ITESM Campus Cuernavaca, Ciudad de México, México

    Manuel Chi-Chim

  3. Mexican Petroleum Institute, Ciudad de México, México

    Leonid Sheremetov

Authors
  1. Juan Frausto-Solís
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  2. Manuel Chi-Chim
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  3. Leonid Sheremetov
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Correspondence to Juan Frausto-Solís.

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Frausto-Solís, J., Chi-Chim, M. & Sheremetov, L. Forecasting Oil Production Time Series with a Population-Based Simulated Annealing Method. Arab J Sci Eng 40, 1081–1096 (2015). https://doi.org/10.1007/s13369-015-1587-z

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  • DOI: https://doi.org/10.1007/s13369-015-1587-z

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